SAM-package: Sparse Additive Modelling

In SAM: Sparse Additive Modelling

Sparse Additive Modelling

Description

SAM provides sparse additive models for high-dimensional prediction tasks (regression and classification). It uses spline basis expansion and efficient optimization routines to compute full regularization paths.

Details

The package exposes four model families:

• samQL: quadratic-loss sparse additive regression.

• samLL: logistic-loss sparse additive classification.

• samHL: hinge-loss sparse additive classification.

• samEL: Poisson-loss sparse additive regression.

All models share a common spline representation and return regularization paths, allowing model selection after one fit.

Author(s)

Tuo Zhao, Xingguo Li, Haoming Jiang, Han Liu, and Kathryn Roeder
Maintainer: Tuo Zhao <[e-mail]>

References

P. Ravikumar, J. Lafferty, H.Liu and L. Wasserman. "Sparse Additive Models", Journal of Royal Statistical Society: Series B, 2009.
T. Zhao and H.Liu. "Sparse Additive Machine", International Conference on Artificial Intelligence and Statistics, 2012.

See Also

samQL,samHL,samLL,samEL

SAM documentation built on Feb. 19, 2026, 5:06 p.m.